In Table REF , we show the impact of the number of synthesized views on performance of stereo matching. The experiment is conducted on Omnidirectional Stereo Dataset [1]} where the left-down view is used for training and testing.
We use the ground truth depth to synthesize multiple novel views on different baseline settings.
Comparing with one novel view, more stereo constraints are brought in when given two or more synthesized views. We observe that there is a performance drop when using four views. As we explored in our analysis in Section REF , when the baseline becomes larger, it introduces more errors in view synthesis. Thus, adding too many synthesized views could accumulate these errors, which could lead to performance drop. Hence in this paper, we choose three synthesized views as the default setting.
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